Case Studies

Projects

A collection of projects that showcase my skills in AI/ML, computer vision, and full-stack development.

Project

AI Study Buddy

Developed an AI-powered study companion to help students understand complex concepts and improve their learning experience.
Features include concept explanation in simple terms, automatic summarization of study notes, and intelligent quiz/flashcard generation.
Solves the problem of finding relevant educational resources and provides on-demand personalized learning support.
Tools used: Streamlit, Python, AI APIs, LLMs.

Project

Developed an automated attendance system using real-time face recognition with Python, OpenCV, and the face recognition library.
Enabled accurate face detection and recognition using ML algorithms; supports capturing faces, marking attendance, and managing data via Pandas.
Built a user-friendly GUI with Tkinter to facilitate registration and attendance tracking, improving efficiency and security in institutional environments.
Tools used: Python, OpenCV, face recognition, Tkinter, Pandas, Pillow, Scikit-learn.

Project

Developed a Tkinter-based AI fitness tracker that securely manages user profiles, calculates BMI, and personalizes workout plans based on fitness goals.
Integrated a Linear Regression model using Scikit-learn to predict daily calorie burn based on historical data.
Features include secure user registration/login, expert health advice based on BMI, calorie logging, and profile update functionality.
Tools used: Python, Tkinter, NumPy, Scikit-learn, JSON.

In-House Project – Jan 2025 to Jan 2026

Building a gesture-based robotic system using MPU-6050 sensor for real-time hand motion detection.
Wireless communication via Zigbee protocol between Arduino Nano (transmitter) and Arduino Mega (receiver).
Technologies: Arduino Nano, Arduino Mega, MPU-6050, Zigbee modules, motor driver, Embedded C.

More projects coming soon • Building and learning every day